Access Control in Cloud Computing using Swarm based Intelligence

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2022 by IJETT Journal
Volume-70 Issue-9
Year of Publication : 2022
Authors : Aparna Manikonda, N. Nalini
DOI : 10.14445/22315381/IJETT-V70I9P217

How to Cite?

Aparna Manikonda, N. Nalini, "Access Control in Cloud Computing using Swarm based Intelligence" International Journal of Engineering Trends and Technology, vol. 70, no. 9, pp. 167-175, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I9P217

Abstract
The new Cloud computing advances stand out due to their Storing ability and minimal expense administrations. The entertainers of the cloud face many issues due to virtualized and adaptable web administrations, which prompts genuine security challenges. Access control is quite possibly the main measure to guarantee distributed computing security. A large portion of the Access control models conceived for Cloud processing is cryptography-based, which leads to overhead with an increased number of users and services. Maintaining a secure, efficient system is important to improve solutions for better success and overhead. In this research, the balance of swarm intelligence and trust is the executives for implementing a novel method in cloud systems. The proposed method has articulated calculations to give better security to implement the reputation system. The outcome shows that this method can ensure better accuracy, accessibility and achievement. /span>

Keywords
Cloud Computing, Access Control, Swarm Intelligence, Trust mechanism, security.

Reference
[1] C. Wang, Q. Wang, K. Ren, and W. Lou, "Ensuring Data Storage Security in Cloud Computing," in Proc. of Iwqos'09, 2009.
[2] Dillon, T., Wu, C., Chang, E, “Cloud Computing: Issues and Challenges,” in: 2010 24th Ieee International Conference on Advanced Information Networking and Applications (Aina). Ieee, pp. 27–33 , 2010.
[3] Krutz, R. L., Vines, R. D, “Cloud Security: A Comprehensive Guide to Secure Cloud Computing,” Wiley Publishing, 2010.
[4] Cai, F., Zhu, N., He, J., Mu, P., Li, W., Yu, Y, “Survey of Access Control Models and Technologies for Cloud Computing,” Clust.Comput. vol. 22, pp.6111–6122, 2019. Https://Doi.Org/10.1007/S10586-018-1850-7
[5] Ghaffar, Z., Ahmed, S., Mahmood, K., Islam, H., Hassan, M., Fortino, G, “An Improved Authentication Scheme for Remote Data Access and Sharing Over Cloud Storage in Cyber-Physical–Socialsystems,” Ieee Access, vol.8, pp.47144–47160 , 2020. Https://Doi.Org/10. 1109/Access.2020.2977264
[6] Ilankumaran, S., Deisy, C., “Multi-Biometric Authentication System Using Finger Vein and Iris in Cloud Computing,” Clust. Comput, vol.22, pp.103–117, 2019.Https://Doi.Org/10.1007/S10586-018-1824-9
[7] Indu, I., Anand, R., Bhaskar, V, “Identity and Access Management in Cloud Environment: Mechanisms and Challenges. Eng. Sci. Technol,” Int. J, vol.21, no.4, pp.574–588, 2018.Https://Doi.Org/10.1016/J.Jestch.2018.05.010
[8] Joseph, T., Kalaiselvan, S.A., Aswathy, S.U., Radhakrishnan, R.,Shamna, A.R, “A Multimodal Biometric Authentication Scheme Based on Feature Fusion for Improving Security in Cloud Environment,” J. Ambient Intell. Humaniz. Comput, 2020.Https://Doi.Org/10.1007/S12652-020-02184-8
[9] Kaur, Gurdip & Khurana, Meenu & Sethi, Monika, “Intrusion Detection System Using Honeypots and Swarm Intelligence,” 2011. 10.1145/2007052.2007060.
[10] V.Meena, N.Dhivya, "An Access Control System in Cloud Storage With Scalable User Revocation for Sharing Data," SSRG International Journal of Computer Science and Engineering, vol.3, no. 9, pp.6-11, 2016. Crossref, Https://Doi.Org/10.14445/23488387/Ijcse-V3i9p102
[11] Reddi Narendra Kumar, Behara Vineela, "An Efficient Multi Authority and Privacy of Data Access Control in the Cloud Storage Systems," SSRG International Journal of Computer Science and Engineering, vol.3, no. 12, pp.10-13, 2016. Crossref, Https://Doi.Org/10.14445/23488387/Ijcse-V3i12p104
[12] Khilar, P., Chaudhari, V., Swain, R, “Trust-Based Access Control in Cloud Computing Using Machine Learning,” in: Das, H., Barik, R., Dubey, H., Roy, D. (Eds) Cloud Computing for Geospatial Big Data Analytics, vol.49, pp. 55–79, 2019. Springer Https://Doi.Org/Https://Doi.Org/10.1007/978-3-030-03359-0_3
[13] G. Lin, D. Wang, Y. Bie and M. Lei, "Mtbac: A Mutual Trust-Based Access Control Model in Cloud Computing," in China Communications, vol. 11, no. 4, pp. 154-162, 2014, Doi: 10.1109/Cc.2014.6827577.
[14] Mehraj, Saima & Banday, M. Tariq, “A Flexible Fine-Grained Dynamic Access Control Approach for Cloud Computing Environment,” Cluster Computing, vol.24, pp.1-22. 10.1007/S10586-020-03196-X.
[15] M. Rafiqul Islam and M. Habiba, "Collaborative Swarm Intelligence Based Trusted Computing," 2012 International Conference on Informatics, Electronics & Vision (Iciev), pp. 1-6, 2012. Doi: 10.1109/Iciev.2012.6317341.
[16] Md. Rafiqul Islam, Mansura Habiba, "Agent Based Framework for Providing Security to Data Storage in Cloud", Computer and Information Technology (Iccit) 2012 15th International Conference on, pp. 446-451, 2012.
[17] Hajivali, Mostafa & Fatemi Moghaddam, Faraz & Alrshdan, Maen & Alothmani, Abdualeem, “Applying An Agent-Based User Authentication and Access Control Model for Cloud Servers,” International Conference on Ict Convergence, pp. 807-812. 10.1109/Ictc.2013.6675484.
[18] S. Kalaivani, A. Vikram and G. Gopinath, "An Effective Swarm Optimization Based Intrusion Detection Classifier System for Cloud Computing," 2019 5th International Conference on Advanced Computing & Communication Systems (Icaccs), 2019, pp. 185-188, Doi: 10.1109/Icaccs.2019.8728450.
[19] Li, X., Zhou, F., Yang, X, “A Multi-Dimensional Trust Evaluation Model for Large-Scale P2p Computing,” J. Parallel Distrib. Comput, vol.71, no.6, pp.837–847, 2011.Https://Doi.Org/10.1016/J.Jpdc.2011.01.007
[20] R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. F. De Rose, and R. Buyya, ”Cloudsim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms,'' Softw.,Pract. Exper., vol. 41, no. 1, pp. 23-50, 2010, Doi: 10.1002/Spe.995.
[21] Elmagzoub, M.A.; Syed, D.; Shaikh, A.; Islam, N.; Alghamdi, A.; Rizwan, S, “A Survey of Swarm Intelligence Based Load Balancing Techniques in Cloud Computing Environment,” Electronics, vol.10, pp.2718, 2021. Https://Doi.Org/10.3390/ Electronics10212718
[22] Pan, I., Elaziz, M.A., & Bhattacharyya, S. (Eds.), “Swarm Intelligence for Cloud Computing (1st Ed.),” Chapman and Hall/Crc, 2020. Https://Doi.Org/10.1201/9780429020582
[23] Lulwah Alsuwaidan, Shakir Khan, Riyad Almakki, Abdul Rauf Baig, Partha Sarkar, Alaa E. S. Ahmed, "Swarm Intelligence Algorithms for Optimal Scheduling for Cloud-Based Fuzzy Systems", Mathematical Problems in Engineering, vol. 2022, Article Id 4255835, pp.11, 2022. Https://Doi.Org/10.1155/2022/4255835
[24] G. Rjoub and J. Bentahar, "Cloud Task Scheduling Based on Swarm Intelligence and Machine Learning," 2017 Ieee 5th International Conference on Future Internet of Things and Cloud (Ficloud), pp. 272-279, 2017. Doi: 10.1109/Ficloud.2017.52.
[25] Marcel Chibuzor Amaechi, Matthias Daniel, Bennett E.O, "Data Storage Management in Cloud Computing Using Deduplication Technique," Ssrg International Journal of Computer Science and Engineering, vol.7, no. 7, pp. 1-7, 2020. Crossref, Https://Doi.Org/10.14445/23488387/Ijcse-V7i7p101
[26] V. A. Lepakshi and C. S. R. Prashanth, "Efficient Resource Allocation With Score for Reliable Task Scheduling in Cloud Computing
Systems," 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (Icimia), 2020, pp. 6-12, Doi: 10.1109/Icimia48430.2020.9074914.
[27] Pushkar G. Dhande, Dr. Bandu B. Meshram, "Extending Uml to Define Access Control," Ssrg International Journal of Computer Science and Engineering, vol. 6, no. 6, pp. 10-16, 2019. Crossref, Https://Doi.Org/10.14445/23488387/Ijcse-V6i6p102
[28] Sinkar Yogita Deepak; C. Rajabhushanam, “Privacy Preservation in Cloud Using Glowworm Swarm-Based Whale Optimization Algorithm (Gwoa) With 128 Key Size in Cleveland Database,” International Journal of Advanced Research in Engineering and Technology (Ijaret), vol.11, no. 3, pp.410-415,2020-03-31,
[29] Thanga Revathi, S., Ramaraj, N. & Chithra, S, “Brain Storm-Based Whale Optimization Algorithm for Privacy-Protected Data Publishing in Cloud Computing,” Cluster Comput, vol. 22, pp.3521–3530, 2019. Https://Doi.Org/10.1007/S10586-018-2200-